How I solved a multiclass imbalance email problem with Logistic Regression

I recall three decades ago when email initially came into being. Emails started out in the offices I worked in at the time and then I eventually obtained my own personal email account, which I still use today. It did not take long for business to take the email and use it for sales and marketing purposes. This competition question I will be discussing discusses emails used for sales and marketing, and whether a person is going to be inclined to open the email and click onto the link in that email. The problem statement for this question entitled, "Lord of the Machine", reads as follows:- "Email marketing is still the most successful marketing channel and the essential element of any digital marketing strategy. Marketers spend a lot of time in writing that perfect email, labouring over each word, catchy layouts on multiple devices to get them best in-industry open rates & click rates. How can I build my campaign to increase the click-through rates of email? It's time to unlock marketing potential and build some exceptional data-science products for email marketing. Analytics Vidhya sends out marketing emailers for various events such as conferences, hackathons, etc. We have provided a sample of user-email interaction data from July 2017 to December 2017. You are required to predict the click probability of links inside a mailer for email campaigns from January 2018 to March 2018" I have written this program using Google Colab, which is a free online Jupyter Notebook that has the major Python libraries already installed.